Pandas Profiling Report

Dataset statistics

Number of variables	12
Number of observations	800
Missing cells	387
Missing cells (%)	4.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	69.7 KiB
Average record size in memory	89.2 B

Variable types

Numeric	8
Categorical	3
Boolean	1

Warnings

`Name` has a high cardinality: 799 distinct values	High cardinality
`#` is highly correlated with `Generation`	High correlation
`Generation` is highly correlated with `#`	High correlation
`Type 2` has 386 (48.2%) missing values	Missing
`#` is uniformly distributed	Uniform
`Name` is uniformly distributed	Uniform
`#` has unique values	Unique

Reproduction

Analysis started	2021-04-08 06:50:41.657851
Analysis finished	2021-04-08 06:50:58.810943
Duration	17.15 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

#
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	800
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	400.5
Minimum	1
Maximum	800
Zeros	0
Zeros (%)	0.0%
Memory size	6.4 KiB

Quantile statistics

Minimum	1
5-th percentile	40.95
Q1	200.75
median	400.5
Q3	600.25
95-th percentile	760.05
Maximum	800
Range	799
Interquartile range (IQR)	399.5

Descriptive statistics

Standard deviation	231.0844002
Coefficient of variation (CV)	0.5769897632
Kurtosis	-1.2
Mean	400.5
Median Absolute Deviation (MAD)	200
Skewness	0
Sum	320400
Variance	53400
Monotocity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
800	1	0.1%
263	1	0.1%
273	1	0.1%
272	1	0.1%
271	1	0.1%
270	1	0.1%
269	1	0.1%
268	1	0.1%
267	1	0.1%
266	1	0.1%
Other values (790)	790	98.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	0.1%
2	1	0.1%
3	1	0.1%
4	1	0.1%
5	1	0.1%

Value	Count	Frequency (%)
800	1	0.1%
799	1	0.1%
798	1	0.1%
797	1	0.1%
796	1	0.1%

Name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	799
Distinct (%)	100.0%
Missing	1
Missing (%)	0.1%
Memory size	6.4 KiB

Gothitelle	1
Flygon	1
Mega Absol	1
Machop	1
Gabite	1
Other values (794)	794

Length

Max length	25
Median length	8
Mean length	8.375469337
Min length	3

Characters and Unicode

Total characters	6692
Distinct characters	60
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	3 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	799 ?
Unique (%)	100.0%

Sample

1st row	Bulbasaur
2nd row	Ivysaur
3rd row	Venusaur
4th row	Mega Venusaur
5th row	Charmander

Value	Count	Frequency (%)
Gothitelle	1	0.1%
Flygon	1	0.1%
Mega Absol	1	0.1%
Machop	1	0.1%
Gabite	1	0.1%
Zapdos	1	0.1%
Talonflame	1	0.1%
Chikorita	1	0.1%
Ledian	1	0.1%
Lillipup	1	0.1%
Other values (789)	789	98.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
mega	48	5.1%
forme	21	2.2%
size	8	0.9%
rotom	6	0.6%
kyurem	5	0.5%
pumpkaboo	4	0.4%
gourgeist	4	0.4%
therian	3	0.3%
deoxys	3	0.3%
wormadam	3	0.3%
Other values (756)	830	88.8%

Most occurring characters

Value	Count	Frequency (%)
a	632	9.4%
e	609	9.1%
o	528	7.9%
r	478	7.1%
i	444	6.6%
n	360	5.4%
l	354	5.3%
t	297	4.4%
u	239	3.6%
s	205	3.1%
Other values (50)	2546	38.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5611	83.8%
Uppercase Letter	937	14.0%
Space Separator	136	2.0%
Other Punctuation	3	< 0.1%
Other Symbol	2	< 0.1%
Dash Punctuation	2	< 0.1%
Decimal Number	1	< 0.1%

Most frequent character per category

Value	Count	Frequency (%)
a	632	11.3%
e	609	10.9%
o	528	9.4%
r	478	8.5%
i	444	7.9%
n	360	6.4%
l	354	6.3%
t	297	5.3%
u	239	4.3%
s	205	3.7%
Other values (17)	1465	26.1%

Value	Count	Frequency (%)
S	129	13.8%
M	120	12.8%
C	62	6.6%
G	58	6.2%
P	56	6.0%
F	50	5.3%
A	47	5.0%
D	47	5.0%
B	45	4.8%
T	44	4.7%
Other values (16)	279	29.8%

Value	Count	Frequency (%)
♀	1	50.0%
♂	1	50.0%

Value	Count	Frequency (%)
.	2	66.7%
'	1	33.3%

Value	Count	Frequency (%)
	136	100.0%

Value	Count	Frequency (%)
2	1	100.0%

Value	Count	Frequency (%)
-	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6548	97.8%
Common	144	2.2%

Most frequent character per script

Value	Count	Frequency (%)
a	632	9.7%
e	609	9.3%
o	528	8.1%
r	478	7.3%
i	444	6.8%
n	360	5.5%
l	354	5.4%
t	297	4.5%
u	239	3.6%
s	205	3.1%
Other values (43)	2402	36.7%

Value	Count	Frequency (%)
	136	94.4%
.	2	1.4%
-	2	1.4%
♀	1	0.7%
♂	1	0.7%
'	1	0.7%
2	1	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6688	99.9%
Misc Symbols	2	< 0.1%
None	2	< 0.1%

Most frequent character per block

Value	Count	Frequency (%)
a	632	9.4%
e	609	9.1%
o	528	7.9%
r	478	7.1%
i	444	6.6%
n	360	5.4%
l	354	5.3%
t	297	4.4%
u	239	3.6%
s	205	3.1%
Other values (47)	2542	38.0%

Value	Count	Frequency (%)
♀	1	50.0%
♂	1	50.0%

Value	Count	Frequency (%)
é	2	100.0%

Type 1
Categorical

Distinct	18
Distinct (%)	2.2%
Missing	0
Missing (%)	0.0%
Memory size	6.4 KiB

Water	112
Normal	98
Grass	70
Bug	69
Psychic	57
Other values (13)	394

Length

Max length	8
Median length	5
Mean length	5.26
Min length	3

Characters and Unicode

Total characters	4208
Distinct characters	28
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Grass
2nd row	Grass
3rd row	Grass
4th row	Grass
5th row	Fire

Value	Count	Frequency (%)
Water	112	14.0%
Normal	98	12.2%
Grass	70	8.8%
Bug	69	8.6%
Psychic	57	7.1%
Fire	52	6.5%
Electric	44	5.5%
Rock	44	5.5%
Ghost	32	4.0%
Dragon	32	4.0%
Other values (8)	190	23.8%

Histogram of lengths of the category

Value	Count	Frequency (%)
water	112	14.0%
normal	98	12.2%
grass	70	8.8%
bug	69	8.6%
psychic	57	7.1%
fire	52	6.5%
rock	44	5.5%
electric	44	5.5%
ghost	32	4.0%
dragon	32	4.0%
Other values (8)	190	23.8%

Most occurring characters

Value	Count	Frequency (%)
r	488	11.6%
a	360	8.6%
o	294	7.0%
e	286	6.8%
c	270	6.4%
s	257	6.1%
i	256	6.1%
t	242	5.8%
l	173	4.1%
g	159	3.8%
Other values (18)	1423	33.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3408	81.0%
Uppercase Letter	800	19.0%

Most frequent character per category

Value	Count	Frequency (%)
r	488	14.3%
a	360	10.6%
o	294	8.6%
e	286	8.4%
c	270	7.9%
s	257	7.5%
i	256	7.5%
t	242	7.1%
l	173	5.1%
g	159	4.7%
Other values (7)	623	18.3%

Value	Count	Frequency (%)
G	134	16.8%
W	112	14.0%
F	100	12.5%
N	98	12.2%
P	85	10.6%
B	69	8.6%
D	63	7.9%
E	44	5.5%
R	44	5.5%
S	27	3.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4208	100.0%

Most frequent character per script

Value	Count	Frequency (%)
r	488	11.6%
a	360	8.6%
o	294	7.0%
e	286	6.8%
c	270	6.4%
s	257	6.1%
i	256	6.1%
t	242	5.8%
l	173	4.1%
g	159	3.8%
Other values (18)	1423	33.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4208	100.0%

Most frequent character per block

Value	Count	Frequency (%)
r	488	11.6%
a	360	8.6%
o	294	7.0%
e	286	6.8%
c	270	6.4%
s	257	6.1%
i	256	6.1%
t	242	5.8%
l	173	4.1%
g	159	3.8%
Other values (18)	1423	33.8%

Type 2
Categorical

MISSING

Distinct	18
Distinct (%)	4.3%
Missing	386
Missing (%)	48.2%
Memory size	6.4 KiB

Flying	97
Ground	35
Poison	34
Psychic	33
Fighting	26
Other values (13)	189

Length

Max length	8
Median length	6
Mean length	5.652173913
Min length	3

Characters and Unicode

Total characters	2340
Distinct characters	28
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Poison
2nd row	Poison
3rd row	Poison
4th row	Poison
5th row	Flying

Value	Count	Frequency (%)
Flying	97	12.1%
Ground	35	4.4%
Poison	34	4.2%
Psychic	33	4.1%
Fighting	26	3.2%
Grass	25	3.1%
Fairy	23	2.9%
Steel	22	2.8%
Dark	20	2.5%
Dragon	18	2.2%
Other values (8)	81	10.1%
(Missing)	386	48.2%

Histogram of lengths of the category

Value	Count	Frequency (%)
flying	97	23.4%
ground	35	8.5%
poison	34	8.2%
psychic	33	8.0%
fighting	26	6.3%
grass	25	6.0%
fairy	23	5.6%
steel	22	5.3%
dark	20	4.8%
dragon	18	4.3%
Other values (8)	81	19.6%

Most occurring characters

Value	Count	Frequency (%)
i	257	11.0%
n	210	9.0%
g	170	7.3%
F	158	6.8%
r	157	6.7%
o	153	6.5%
y	153	6.5%
s	131	5.6%
l	129	5.5%
c	106	4.5%
Other values (18)	716	30.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1926	82.3%
Uppercase Letter	414	17.7%

Most frequent character per category

Value	Count	Frequency (%)
i	257	13.3%
n	210	10.9%
g	170	8.8%
r	157	8.2%
o	153	7.9%
y	153	7.9%
s	131	6.8%
l	129	6.7%
c	106	5.5%
a	104	5.4%
Other values (7)	356	18.5%

Value	Count	Frequency (%)
F	158	38.2%
G	74	17.9%
P	67	16.2%
D	38	9.2%
S	22	5.3%
I	14	3.4%
R	14	3.4%
W	14	3.4%
E	6	1.4%
N	4	1.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2340	100.0%

Most frequent character per script

Value	Count	Frequency (%)
i	257	11.0%
n	210	9.0%
g	170	7.3%
F	158	6.8%
r	157	6.7%
o	153	6.5%
y	153	6.5%
s	131	5.6%
l	129	5.5%
c	106	4.5%
Other values (18)	716	30.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2340	100.0%

Most frequent character per block

Value	Count	Frequency (%)
i	257	11.0%
n	210	9.0%
g	170	7.3%
F	158	6.8%
r	157	6.7%
o	153	6.5%
y	153	6.5%
s	131	5.6%
l	129	5.5%
c	106	4.5%
Other values (18)	716	30.6%

HP
Real number (ℝ_≥0)

Distinct	94
Distinct (%)	11.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	69.25875
Minimum	1
Maximum	255
Zeros	0
Zeros (%)	0.0%
Memory size	6.4 KiB

Quantile statistics

Minimum	1
5-th percentile	35.95
Q1	50
median	65
Q3	80
95-th percentile	110
Maximum	255
Range	254
Interquartile range (IQR)	30

Descriptive statistics

Standard deviation	25.53466903
Coefficient of variation (CV)	0.368685098
Kurtosis	7.232078374
Mean	69.25875
Median Absolute Deviation (MAD)	15
Skewness	1.568224376
Sum	55407
Variance	652.0193226
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
60	67	8.4%
50	63	7.9%
70	57	7.1%
65	46	5.8%
75	43	5.4%
80	43	5.4%
40	38	4.8%
45	38	4.8%
55	37	4.6%
100	32	4.0%
Other values (84)	336	42.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	1	0.1%
10	1	0.1%
20	6	0.8%
25	2	0.2%
28	1	0.1%

Value	Count	Frequency (%)
255	1	0.1%
250	1	0.1%
190	1	0.1%
170	1	0.1%
165	1	0.1%

Attack
Real number (ℝ_≥0)

Distinct	111
Distinct (%)	13.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	79.00125
Minimum	5
Maximum	190
Zeros	0
Zeros (%)	0.0%
Memory size	6.4 KiB

Quantile statistics

Minimum	5
5-th percentile	30
Q1	55
median	75
Q3	100
95-th percentile	136.2
Maximum	190
Range	185
Interquartile range (IQR)	45

Descriptive statistics

Standard deviation	32.45736587
Coefficient of variation (CV)	0.4108462318
Kurtosis	0.1697173149
Mean	79.00125
Median Absolute Deviation (MAD)	20
Skewness	0.551613748
Sum	63201
Variance	1053.480599
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
100	40	5.0%
65	39	4.9%
80	37	4.6%
50	37	4.6%
85	33	4.1%
60	33	4.1%
75	32	4.0%
70	31	3.9%
90	30	3.8%
55	30	3.8%
Other values (101)	458	57.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5	2	0.2%
10	3	0.4%
15	1	0.1%
20	8	1.0%
22	1	0.1%

Value	Count	Frequency (%)
190	1	0.1%
185	1	0.1%
180	3	0.4%
170	2	0.2%
165	3	0.4%

Defense
Real number (ℝ_≥0)

Distinct	103
Distinct (%)	12.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	73.8425
Minimum	5
Maximum	230
Zeros	0
Zeros (%)	0.0%
Memory size	6.4 KiB

Quantile statistics

Minimum	5
5-th percentile	35
Q1	50
median	70
Q3	90
95-th percentile	130
Maximum	230
Range	225
Interquartile range (IQR)	40

Descriptive statistics

Standard deviation	31.18350056
Coefficient of variation (CV)	0.422297465
Kurtosis	2.72626036
Mean	73.8425
Median Absolute Deviation (MAD)	20
Skewness	1.155912303
Sum	59074
Variance	972.4107071
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
70	54	6.8%
50	49	6.1%
60	46	5.8%
80	39	4.9%
40	36	4.5%
65	36	4.5%
90	35	4.4%
100	33	4.1%
55	32	4.0%
45	32	4.0%
Other values (93)	408	51.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5	2	0.2%
10	1	0.1%
15	4	0.5%
20	4	0.5%
23	1	0.1%

Value	Count	Frequency (%)
230	3	0.4%
200	2	0.2%
184	1	0.1%
180	3	0.4%
168	1	0.1%

Sp. Atk
Real number (ℝ_≥0)

Distinct	105
Distinct (%)	13.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	72.82
Minimum	10
Maximum	194
Zeros	0
Zeros (%)	0.0%
Memory size	6.4 KiB

Quantile statistics

Minimum	10
5-th percentile	30
Q1	49.75
median	65
Q3	95
95-th percentile	131.05
Maximum	194
Range	184
Interquartile range (IQR)	45.25

Descriptive statistics

Standard deviation	32.72229417
Coefficient of variation (CV)	0.4493586126
Kurtosis	0.2978936607
Mean	72.82
Median Absolute Deviation (MAD)	20
Skewness	0.7446624978
Sum	58256
Variance	1070.748536
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
60	51	6.4%
40	49	6.1%
65	44	5.5%
50	39	4.9%
55	35	4.4%
45	33	4.1%
70	30	3.8%
35	29	3.6%
85	27	3.4%
80	27	3.4%
Other values (95)	436	54.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10	3	0.4%
15	4	0.5%
20	8	1.0%
23	1	0.1%
24	2	0.2%

Value	Count	Frequency (%)
194	1	0.1%
180	3	0.4%
175	1	0.1%
170	3	0.4%
165	2	0.2%

Sp. Def
Real number (ℝ_≥0)

Distinct	92
Distinct (%)	11.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	71.9025
Minimum	20
Maximum	230
Zeros	0
Zeros (%)	0.0%
Memory size	6.4 KiB

Quantile statistics

Minimum	20
5-th percentile	32.95
Q1	50
median	70
Q3	90
95-th percentile	120
Maximum	230
Range	210
Interquartile range (IQR)	40

Descriptive statistics

Standard deviation	27.8289158
Coefficient of variation (CV)	0.3870368318
Kurtosis	1.628394057
Mean	71.9025
Median Absolute Deviation (MAD)	20
Skewness	0.8540186115
Sum	57522
Variance	774.4485544
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
80	52	6.5%
50	50	6.2%
55	47	5.9%
65	44	5.5%
60	43	5.4%
75	40	5.0%
70	40	5.0%
90	36	4.5%
45	35	4.4%
85	30	3.8%
Other values (82)	383	47.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
20	6	0.8%
23	1	0.1%
25	11	1.4%
30	20	2.5%
31	1	0.1%

Value	Count	Frequency (%)
230	1	0.1%
200	1	0.1%
160	2	0.2%
154	3	0.4%
150	7	0.9%

Speed
Real number (ℝ_≥0)

Distinct	108
Distinct (%)	13.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	68.2775
Minimum	5
Maximum	180
Zeros	0
Zeros (%)	0.0%
Memory size	6.4 KiB

Quantile statistics

Minimum	5
5-th percentile	25
Q1	45
median	65
Q3	90
95-th percentile	115
Maximum	180
Range	175
Interquartile range (IQR)	45

Descriptive statistics

Standard deviation	29.06047372
Coefficient of variation (CV)	0.4256229903
Kurtosis	-0.2364366728
Mean	68.2775
Median Absolute Deviation (MAD)	21
Skewness	0.3579332951
Sum	54622
Variance	844.5111327
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50	46	5.8%
60	44	5.5%
70	37	4.6%
65	36	4.5%
30	35	4.4%
80	33	4.1%
40	32	4.0%
90	31	3.9%
100	31	3.9%
55	30	3.8%
Other values (98)	445	55.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
5	2	0.2%
10	3	0.4%
15	9	1.1%
20	15	1.9%
22	1	0.1%

Value	Count	Frequency (%)
180	1	0.1%
160	1	0.1%
150	4	0.5%
145	3	0.4%
140	2	0.2%

Generation
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	6
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	3.32375
Minimum	1
Maximum	6
Zeros	0
Zeros (%)	0.0%
Memory size	6.4 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	2
median	3
Q3	5
95-th percentile	6
Maximum	6
Range	5
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	1.6612904
Coefficient of variation (CV)	0.4998241145
Kurtosis	-1.239575758
Mean	3.32375
Median Absolute Deviation (MAD)	2
Skewness	0.01425810028
Sum	2659
Variance	2.759885795
Monotocity	Increasing

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
1	166	20.8%
5	165	20.6%
3	160	20.0%
4	121	15.1%
2	106	13.2%
6	82	10.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	166	20.8%
2	106	13.2%
3	160	20.0%
4	121	15.1%
5	165	20.6%

Value	Count	Frequency (%)
6	82	10.2%
5	165	20.6%
4	121	15.1%
3	160	20.0%
2	106	13.2%

Legendary
Boolean

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	928.0 B

False	735
True	65

Common Values
Chart

Value	Count	Frequency (%)
False	735	91.9%
True	65	8.1%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	#	Name	Type 1	Type 2	HP	Attack	Defense	Sp. Atk	Sp. Def	Speed	Generation	Legendary
0	1	Bulbasaur	Grass	Poison	45	49	49	65	65	45	1	False
1	2	Ivysaur	Grass	Poison	60	62	63	80	80	60	1	False
2	3	Venusaur	Grass	Poison	80	82	83	100	100	80	1	False
3	4	Mega Venusaur	Grass	Poison	80	100	123	122	120	80	1	False
4	5	Charmander	Fire	NaN	39	52	43	60	50	65	1	False
5	6	Charmeleon	Fire	NaN	58	64	58	80	65	80	1	False
6	7	Charizard	Fire	Flying	78	84	78	109	85	100	1	False
7	8	Mega Charizard X	Fire	Dragon	78	130	111	130	85	100	1	False
8	9	Mega Charizard Y	Fire	Flying	78	104	78	159	115	100	1	False
9	10	Squirtle	Water	NaN	44	48	65	50	64	43	1	False

Last rows

	#	Name	Type 1	Type 2	HP	Attack	Defense	Sp. Atk	Sp. Def	Speed	Generation	Legendary
790	791	Noibat	Flying	Dragon	40	30	35	45	40	55	6	False
791	792	Noivern	Flying	Dragon	85	70	80	97	80	123	6	False
792	793	Xerneas	Fairy	NaN	126	131	95	131	98	99	6	True
793	794	Yveltal	Dark	Flying	126	131	95	131	98	99	6	True
794	795	Zygarde Half Forme	Dragon	Ground	108	100	121	81	95	95	6	True
795	796	Diancie	Rock	Fairy	50	100	150	100	150	50	6	True
796	797	Mega Diancie	Rock	Fairy	50	160	110	160	110	110	6	True
797	798	Hoopa Confined	Psychic	Ghost	80	110	60	150	130	70	6	True
798	799	Hoopa Unbound	Psychic	Dark	80	160	60	170	130	80	6	True
799	800	Volcanion	Fire	Water	80	110	120	130	90	70	6	True

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows